This invention relates to a method for detecting motion from a video signal having noise or flicker superposed and a noise reducer for decreasing a noise component utilizing a frame correlation of the video signal and improving a signal-to-noise ratio of the video signal.
Generally, the video signal is a signal which has video information repeating at the periods of the frames, and there is high auto-correlation between the frames On the other hand, since the noise component included in the video signal normally has little auto-correlation, if the video signal is averaged temporally for each frame period, the energy of the signal component hardly changes, and therefore, only the energy of the noise component decreases, so that the noise can be reduced. In order to obtain the above-mentioned average, a plurality of frame memories are required. Because the frame memories are expensive, the generally practiced method is not to use a non-recursive filter which requires a plurality of frame data but to use a one-frame first-order recursive filter.
With regard to the noise reducer of a frame-cyclic arrangement which reduces noise by utilizing the frame correlation of the video signal, many methods have been proposed. One of those methods which describes the basic concept is carried in the Journal of the Institute of Television Engineers of Japan Vol. 33, No. 4 (1979).
To help understand the present invention, description will first be made of a conventional noise reducer referring to FIG. 1. In FIG. 1, an input video signal 1, which comprises a component signal such as a luminance signal or one of color difference signals, primary color signal R, G and B, is supplied to the input terminal The input video signal 1 supplied through the input terminal is attenuated to (1-K) times the original energy by a variable attenuator 2 and becomes an input attenuated video signal 3, which is applied to an adder 4. On the other hand, a previous video signal 7, which has had noise reduced and then delayed by one frame period, is attenuated to K times the energy level held theretofore by a variable attenuator 8 and becomes a previous-frame-attenuated video signal 9. This video signal 9 is added with the input attenuated video signal 3 by the adder 4, and output as an output video signal 5 from an output terminal, and then stored in a frame memory 6.
When the input video signal 1 is a completely still image, the frequency spectrum of this video signal is a line spectrum with a 30-Hz period, there is no energy loss of video signal by the circuit as shown in FIG. 1, and the degree of improvement in the signal-to-noise ratio can be expressed as follows: EQU Improvement of signal-to-noise ratio=10 log (1+K)/(1-K) (dB)(Eq. 1)
FIG. 2 shows changes in the improvement in the signal-to-noise ratio with respect to coefficient K. It is obvious that the larger the K, the greater the degree of improvement in the signal-to-noise ratio becomes.
On the other hand, generally, there is motion in the video signal, and if an image including motion is passed through the circuit in FIG. 1, an after image persists. The time constant T of the after image is EQU T=-1/(1n K) x 1/30 (sec) (Eq. 2)
FIG. 3 shows after-image time constant characteristics with respect to the coefficient K. The after-image time constant T, namely, the after image is larger with a larger K.
That is to say, the improvement of the signal-to-noise ratio and the occurrence of the after image are shadows to each other. For this reason, generally, the coefficient K is varied in the range of 0&lt;K&lt;1 according to the motion of the input video signal. To be more specific, when the motion of the video signal is large, the K is reduced to suppress the after image, and when the motion is small, the K is increased, thereby increasing the degree of improvement of the signal-to-noise ratio. This control of the K is done by a coefficient control circuit 10.
From the input video signal 1 from the input terminal, the subtracter subtracts the previous frame video signal 7 which has had noise reduced and has been delayed by one frame period, and a resulting inter-frame difference signal .DELTA. is input into the coefficient control circuit 10. The probability of the inter-frame difference signal .DELTA. being a noise component is generally high for smaller inter-frame difference signal .DELTA., while the probability of the inter-frame difference signal .DELTA. being a motion component of the signal is high for larger inter-frame difference signal .DELTA.. Therefore, when the inter-frame difference signal .DELTA. is small, the K is increased to increase the degree of improvement of the signal-to-noise ratio. When the inter-frame difference signal .DELTA. is large, the K is decreased to suppress an occurrence of the after image insofar as possible.
The value of K is controlled as shown in FIG. 4 according to the inter-frame difference signal .DELTA. input to the coefficient control circuit 10.
In FIG. 4, the K is a function of the inter-frame difference signal .DELTA., and can be expressed by Eq. 3 below. ##EQU1##
Thus, by the conventional method, it is possible to reduce noise while minimizing the occurrence of the after image.
On the other hand, a method for detecting motion from a noise-superposed video signal has been reported in ITEJ Technical Report TEBS112-1 (1986, 7, 27). This method will be described with reference to FIGS. 5 and 6, and Table 1.
FIG. 5 indicates the relation between noise and a motion signal The frequency of zero cross of the inter-frame difference signal .DELTA. including noise is considered to differ in the still-image region and in the moving-image region. By utilizing this phenomenon, the motion is detected as follows
With the inter-frame difference signal .DELTA. at a target pixel for motion detection and the preset surrounding pixels around the center target pixel in the detection range, the number of plus pixels CP and the number of minus pixels CN are calculated, and .xi. is calculated by the following equation. EQU .xi.=min (CP, CN)/max (CP, CN) (Eq. 4)
where
min (A, B) : a value of A or B whichever is smaller PA0 max (A, B) : a value of A or B whichever is larger
In comparing .xi. with a preset threshold value th (0&lt;.xi.th&lt;1), when 0.ltoreq..xi..ltoreq..xi.th, a decision as "motion" is made, and when .xi.th&lt;.xi.&lt;1, a decision as "still" is made.
Table 1 shows a summary of correspondence between the values of .xi. and the decision results in the motion detection when the range of the surrounding pixels, by which the decision was made, was set as 5.times.5 pixels around the center target pixel as shown in FIG. 6 and the threshold value was .xi.th=0.35. In the case of FIG. 6, since CP=16 and CN=9, .xi.=0.56, so that decision was "still".
TABLE 1 ______________________________________ plus minus (CP) (CN) .xi. decision ______________________________________ 0 25 0 motion 1 24 0.04 motion 2 23 0.09 motion 3 22 0.14 motion 4 21 0.19 motion 5 20 0.25 motion 6 19 0.32 motion 7 18 0.39 still 8 17 0.47 still 9 16 0.56 still 10 15 0.59 still 11 14 0.67 still 12 13 0.92 still 13 12 0.92 still 14 11 0.67 still 15 10 0.59 still 16 9 0.56 still 17 8 0.47 still 18 7 0.39 still 19 6 0.32 still 20 5 0.25 motion 21 4 0.19 motion 22 3 0.14 motion 23 2 0.09 motion 24 1 0.24 motion 25 0 0 motion ______________________________________
As described above, by the conventional motion detection method, a decision can be made as to the motion based on the inter-frame difference signal at the center pixel as the target of motion detection and the surrounding pixels in the preset detection range.
However, in the above-mentioned conventional noise reducer, noise reduction is performed by using only a statistical feature that the inter-frame difference signal .DELTA. is highly likely to be a noise component when the inter-frame difference signal .DELTA. is smaller, while the inter-frame difference signal .DELTA. is highly likely to be a motion component when the inter-frame difference signal .DELTA. is larger. So, this is not motion detection in the strict sensor of the word. By this method, a small motion in the inter-frame difference signal .DELTA. is removed in the same way as noise. This removal of small motion causes an after image to occur in the moving image, which has been a problem.
The conventional motion detection method has another problem in which an omission of detecting the motion such as misjudging the motion as a still or an error such as misjudging the still as a motion occur very often owing to the effects of noise and flicker.